A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study

This article presents a flood risk analysis model that considers the spatially heterogeneous nature of flood events. The basic concept of this approach is to generate a large sample of flood events that can be regarded as temporal extrapolation of flood events. These are combined with cumulative flood impact indicators, such as building damages, to finally derive time series of damages for risk estimation. Therefore, a multivariate modeling procedure that is able to take into account the spatial characteristics of flooding, the regionalization method top‐kriging, and three different impact indicators are combined in a model chain. Eventually, the expected annual flood impact (e.g., expected annual damages) and the flood impact associated with a low probability of occurrence are determined for a study area. The risk model has the potential to augment the understanding of flood risk in a region and thereby contribute to enhanced risk management of, for example, risk analysts and policymakers or insurance companies. The modeling framework was successfully applied in a proof‐of‐concept exercise in Vorarlberg (Austria). The results of the case study show that risk analysis has to be based on spatially heterogeneous flood events in order to estimate flood risk adequately.     

The identification of logistic regression models with errors in the variables

The simple logistic regression model with normal measurement error and normal regressor is shown to be identifiable without any extra information about the measurement error. The multiple logistic regression model with more than one regressor variable measured with error is not identifiable. If the covariance matrix of the measurement error is known up to a scalar factor, the model is identified. Further we discuss why in spite of the identifiability the models cannot be estimated in a reasonable way without extra information about the measurement error.     

On social work and what gender has got to do with it

Living in gendered societies makes it necessary to take into account the specific ways in which social problems and social issues affect the lives of women and men, girls and boys. Not only are social problems and social issues very often gender biased; this is also true for the professions dealing with these problems and issues, and for the training programmes for professions like social work. Sociological analysis of society and philosophical understanding of a good life are permeated by gender-specific perceptions -- often without those involved being aware of them. Furthermore, social policies reinforce gender-specific biases because they are based on gender-specific (i.e. male) standards. Gender as an analytical category has been brought into scientific and public discourse by feminist theoreticians and activists making women -- and thus also men -- visible with regard to structure and subject issues. The development of gender theory and research highlights the significance of gender arrangements to understand social phenomena and to support gender-equality ways of thinking and policies. At the same time, men and women are not only confronted with gendered structures, but via socialization processes and personal development they also reproduce these gender differences in their daily lives by 'doing gender'.     

Editorial

Ohne Zusammenfassung

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Editorial

     

Führung durch Selbstführung

This paper outlines the conceptual bases, strategies, and psychological attributes of leadership by self-leadership. In addition, relations to other theories of leadership are drawn. Dimensions and correlates of self-leadership competence are described and discussed. Various approaches for developing self-leadership competence are discussed as well.     

The Determinants of Racial Disparities in Perceived Job Insecurity: A Test of Three Perspectives

Why do African Americans report higher levels of perceived job insecurity than whites? We analyze data from the 1996 and 1998 General Social Survey to test alternative predictions from the compositional, inclusive‐discrimination, and dispositional perspectives concerning the sources of the racial gap in perceived insecurity. Results from ordered probit regressions provide most support for the inclusive‐discrimination perspective, which maintains that employment practices associated with “modern racial prejudice” induce perceived insecurity on a widespread and generalized basis among African Americans. Accordingly, compared to whites, African Americans experience perceived insecurity net of human capital credentials and job/labor market characteristics. Additional analyses provide one qualification to these findings: dynamics associated with the inclusive‐discrimination perspective are more pronounced in the private sector than the public sector.     

The Impact of Items and Anchors on Parent–Child Reports of Problem Behavior

Research has repeatedly demonstrated that parent and child reports of child behavior and emotional functioning often do not agree in terms of symptom severity or even symptom presence. Given the potential clinical impact that discrepant reports may have on the therapeutic process, a significant amount of research has addressed the factors influencing this observed discrepancy. Traditionally, this research has evaluated the impact of demographic factors on mean differences and obtained correlation coefficients between parent and child reports. The current research improves upon previous research in this area in two ways. First, the current research uses parent and child measures with identical rather than similar items as is commonly found in previous research. Second, the current research moves beyond identifying demographic influences on discrepant reports by explaining observed discrepancies in terms of differences in parent and child perceptions of typical child behavior.David Carlston and Benjamin Ogles are affiliated with Department of Psychology, Ohio University, Athens, USA.Funding for this project was provided by the Ohio Department of Mental Health.